Machine learning to find drivers of an event with presence-only data (no absence)
Yes.

Since you have only one type of data, cluster analysis may be a good choice. 

You can also try '1-class learning' approaches, although I have found these to be unreliable in the past. 

An example of a cluster analysis algorithm in R is kmeans. There are many others. These approaches will reveal points that typify large portions of the dataset. By examining 'typical' cases, and how they differ, you can spot potential causal factors to test experimentally.

An example of a 1-class learning algorithm is a one-class svm. Most svm libraries will accept data of a single class and do the right thing with it. Here's an example with R's e1071 package.